R Notebook

library(tidyverse)
library(here)
library(readxl)

Warning: package ‘readxl’ was built under R version 4.2.3

library(janitor)

armor <- clean_names(read_xlsx(here("raw_data/armour.xlsx")))

Error in exists(cacheKey, where = .rs.WorkingDataEnv, inherits = FALSE) : 
  invalid first argument
Error in assign(cacheKey, frame, .rs.CachedDataEnv) : 
  attempt to use zero-length variable name

sets <- clean_names(read_xlsx(here("raw_data/armour.xlsx"), sheet = 2))
all_items <- clean_names(read_xlsx(here("raw_data/all_crafting.xlsx")))

sets

cleaned_armor <- all_items %>% 
  mutate(across(where(is.character), ~ str_to_lower(.x))) %>% 
  select(-c(description, set_bonus)) %>% 
  right_join(armor, by = join_by(item, upgrade_level)) %>% 
  left_join(sets) %>% 
  group_by(item, type, crafting_station_level, crafting_station, upgrade_level,
           armor, resistant, weak, set, weight, speed, other, bonus) %>% 
  summarise(materials = toString(unique(material)),
            material_amounts = toString(amount_of_material)) %>% 
  pivot_wider(names_from = crafting_station, values_from = crafting_station_level) %>% 
  clean_names()

Joining with `by = join_by(set)``summarise()` has grouped output by 'item', 'type', 'crafting_station_level', 'crafting_station', 'upgrade_level', 'armor', 'resistant', 'weak', 'set', 'weight', 'speed', 'other'. You can override using the `.groups` argument.

armour %>% 
  filter(upgrade_level == 1) %>% 
  select(item, armor, weight)

types <- all_items %>% 
  select(item, type) %>% 
  filter(type != "upgrade") %>% 
  distinct()

armour_type <- armour %>% 
  left_join(types)

armour_type %>% 
  filter(type == "cape" & upgrade_level == 1) %>% 
  select(item, armor, weight, speed, resistant, weak)

armor <- read_csv(here("clean_data/armor_data.csv"))

armor %>% 
  rename("upgrade_level" = "Upgrade Level") %>% 
  filter(Type == "Chest" & upgrade_level == 1) %>% 
  select(Item, Armor, Weight, Speed, Resistant, Weak)

names(armor)

armor <- armor %>% 
  clean_names() %>% 
  mutate(across(where(is.character), ~ str_to_lower(.x)))

crafting_armor <- all_items %>% 
  semi_join(armor, join_by(item)) %>% 
  mutate(across(where(is.character), ~ str_to_lower(.x)))

crafting_armor %>% 
  pivot_wider(names_from = crafting_station, values_from = crafting_station_level) %>% 
  clean_names() %>% 
  filter(is.na(workbench) | workbench <= 6) %>% 
  filter(is.na(forge) | forge <= 7) %>%
  filter(is.na(galdr_table) | galdr_table <= 0) %>%
  filter(is.na(black_forge) | black_forge <= 0)

chest_list <- cleaned_armor %>% 
  filter(type == "chest") %>% 
  select(item) %>% 
  pull()

Adding missing grouping variables: `type`, `upgrade_level`, `armor`, `resistant`, `weak`, `set`, `weight`, `speed`, `other`

p <- armor_list %>% 
  filter(item %in% chest_list) %>%
  group_by(item) %>% 
  filter(upgrade_level == max(upgrade_level)) %>% 
  arrange(desc(armor)) %>% 
  head(5) %>% 
  select(item, upgrade_level, armor, weight) %>%

  pivot_longer(c(armor, weight), names_to = "stat", values_to = "value") %>% 
  mutate(item = str_to_title(item),
         stat = str_to_title(stat)) %>%
  unite("item", item:upgrade_level, sep = " - Level ",  remove = TRUE) %>% 
  ggplot(aes(item, value, fill = stat)) +
  geom_col(position = "dodge") +
  theme_classic() +
  theme(text = element_text(colour = "black"),
        axis.text = element_text(colour = "black"),
        legend.background = element_rect(fill = "transparent"),
        panel.background = element_rect(fill = "transparent"),
        panel.border = element_rect(fill = "transparent",
                                    colour = "transparent"),
        plot.background = element_rect(fill = "transparent",
                                       colour = NA),
        axis.text.x = element_text(angle = 45, hjust = 1)) +
  labs(
    x = "Chest",
    y = "Stat",
    fill = ""
  ) 
ggplotly(p)